Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 314 565 513 700 529 625 55 279 927 423 49 237 470 47 607 883 234 516 636 326
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 529 927 326 423 NA 55 607 565 49 47 237 234 NA 513 314 NA 883 279 636 700 516 625 470
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 2 1 3 4 2 3 3 4 5
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y"
[26] "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y"
[26] "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "p" "c" "q" "e" "m" "W" "O" "E" "N" "B"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 9
which( manyNumbersWithNA > 900 )
[1] 2
which( is.na( manyNumbersWithNA ) )
[1] 5 13 16
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 927
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 927
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 927
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "W" "O" "E" "N" "B"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "p" "c" "q" "e" "m"
manyNumbers %in% 300:600
[1] TRUE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[18] TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 1 2 3 5 10 13 18 20
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "large" "small" "small" NA "small" "large" "large" "small" "small" "small" "small"
[13] NA "large" "small" NA "large" "small" "large" "large" "large" "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "large" "small" "small" "UNKNOWN" "small" "large" "large" "small" "small"
[11] "small" "small" "UNKNOWN" "large" "small" "UNKNOWN" "large" "small" "large" "large"
[21] "large" "large" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 529 927 0 0 NA 0 607 565 0 0 0 0 NA 513 0 NA 883 0 636 700 516 625 0
unique( duplicatedNumbers )
[1] 3 2 1 4 5
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 2 1 4 5
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE
which.max( manyNumbersWithNA )
[1] 2
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 927
which.min( manyNumbersWithNA )
[1] 10
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 47
range( manyNumbersWithNA, na.rm = TRUE )
[1] 47 927
manyNumbersWithNA
[1] 529 927 326 423 NA 55 607 565 49 47 237 234 NA 513 314 NA 883 279 636 700 516 625 470
sort( manyNumbersWithNA )
[1] 47 49 55 234 237 279 314 326 423 470 513 516 529 565 607 625 636 700 883 927
sort( manyNumbersWithNA, na.last = TRUE )
[1] 47 49 55 234 237 279 314 326 423 470 513 516 529 565 607 625 636 700 883 927 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 927 883 700 636 625 607 565 529 516 513 470 423 326 314 279 237 234 55 49 47 NA NA NA
manyNumbersWithNA[1:5]
[1] 529 927 326 423 NA
order( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
rank( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
sort( mixedLetters )
[1] "B" "c" "e" "E" "m" "N" "O" "p" "q" "W"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 3.0 9.0 3.0 5.0 3.0 6.5 9.0 1.0 6.5 9.0
rank( manyDuplicates, ties.method = "min" )
[1] 2 8 2 5 2 6 8 1 6 8
rank( manyDuplicates, ties.method = "random" )
[1] 3 8 2 5 4 7 9 1 6 10
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 -0.4625066 1.0000197 1.1298453 -0.9166387
[10] 0.6870685 0.7110857 0.9595941 -1.8271069 0.5652537 -0.4595038
round( v, 0 )
[1] -1 0 0 0 1 0 1 1 -1 1 1 1 -2 1 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.5 1.0 1.1 -0.9 0.7 0.7 1.0 -1.8 0.6 -0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.46 1.00 1.13 -0.92 0.69 0.71 0.96 -1.83 0.57 -0.46
floor( v )
[1] -1 -1 0 0 1 -1 1 1 -1 0 0 0 -2 0 -1
ceiling( v )
[1] -1 0 0 1 1 0 2 2 0 1 1 1 -1 1 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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